pandas.core.groupby.DataFrameGroupBy.idxmin()非常慢，如何使我的代码更快? [英] pandas.core.groupby.DataFrameGroupBy.idxmin() is very slow , how can i make my code faster?

问题描述

我正在尝试执行与SQL group by相同的操作并采用最小值:

i am trying to do same action as SQL group by and take min value :

select id,min(value) ,other_fields...
from table
group by ('id')

我尝试过:

dfg = df.groupby('id', sort=False)
idx = dfg['value'].idxmin()
df = df.loc[idx, list(df.columns.values)]

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.groupby.DataFrameGroupBy.idxmin.html 但是第2行，idxmin()在df中的〜4M列上花费了超过半小时，其中group by花费了不到1秒，我想念的是要花费这么长时间吗?如何使这个过程更快?在纯SQL中会更快吗?

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.groupby.DataFrameGroupBy.idxmin.html but line 2 the idxmin() is taking more than half hour on ~4M columns in df where the group by takes less than 1 second , what am i missing is it suppose to take that long ? how can make this process faster ? will it be faster in pure SQL ?

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